Triple

T4750839
Position Surface form Disambiguated ID Type / Status
Subject The Great Wall (2016 film) E105472 entity
Predicate starring P1507 FINISHED
Object Lu Han E388180 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lu Han | Statement: [The Great Wall (2016 film), starring, Lu Han]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lu Han
Context triple: [The Great Wall (2016 film), starring, Lu Han]
  • A. Lu Han
    Lu Han was a prominent Chinese Nationalist general and warlord who controlled Yunnan province during the Republican era and played a key role in the Second Sino-Japanese War.
  • B. Kris Wu chosen
    Kris Wu is a Chinese-Canadian singer, rapper, actor, and former member of the K-pop group EXO who later pursued a solo entertainment career in China and internationally.
  • C. Haifan Lin
    Haifan Lin is a prominent stem cell and developmental biologist known for his pioneering research on germline stem cells and RNA regulation.
  • D. Lu Jun
    Lu Jun is a family member of Lu Lingzi, the Chinese graduate student who was killed in the 2013 Boston Marathon bombing.
  • E. Li Weihan
    Li Weihan was a prominent Chinese Communist revolutionary and politician who played key roles in party organization and United Front work in the early and mid-20th century.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69bd43f07fa48190954317d01600994a completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd64c97b548190815083f2f8df907c completed March 20, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69be3a561a7c8190a5ab87751ab36e0d completed March 21, 2026, 6:27 a.m.
Created at: March 20, 2026, 1:20 p.m.